Enhanced Control of Nonlinear Systems Under Control Input Constraints and Faults: A Neural Network-Based Integral Fuzzy Sliding Mode Approach.

Many existing control techniques proposed in the literature tend to overlook faults and physical limitations in the systems, which significantly restricts their applicability to practical, real-world systems. Consequently, there is an urgent necessity to advance the control and synchronization of such systems in real-world scenarios, specifically when faced with the challenges posed by faults and physical limitations in their control actuators. Motivated by this, our study unveils an innovative control approach that combines a neural network-based sliding mode algorithm with fuzzy logic systems to handle nonlinear systems.

Enhancing Medical Signal Processing and Diagnosis with AI-Generated Content Techniques.

In medical diagnostics, the accurate classification and analysis of biomedical signals play a crucial role, particularly in the diagnosis of neurological disorders such as epilepsy. Electroencephalogram (EEG) signals, which represent the electrical activity of the brain, are fundamental in identifying epileptic seizures. However, challenges such as data scarcity and imbalance significantly hinder the development of robust diagnostic models.

Comparison of 5-Year Follow-up Outcomes Between Primary and Revision Roux-en-Y Gastric Bypasses After Open Vertical Banded Gastroplasty: an Inverse Propensity Score-Weighted Analysis.

Introduction: Vertical banded gastroplasty (VBG) is associated with high weight regain; Roux-en-Y gastric bypass (RYGB) is used as a revision procedure in patients with VBG experiencing weight regain. This study compared the 5-year follow-up outcomes of primary (PRYGB) and revision RYGB after VBG (RRYGB).

Methods: Patients who underwent PRYGB or RRYGB after VBG from 2008 to 2016 were enrolled.

Chaos in Cancer Tumor Growth Model with Commensurate and Incommensurate Fractional-Order Derivatives.

Analyzing the dynamics of tumor-immune systems can play an important role in the fight against cancer, since it can foster the development of more effective medical treatments. This paper was aimed at making a contribution to the study of tumor-immune dynamics by presenting a new model of cancer growth based on fractional-order differential equations. By investigating the system dynamics, the manuscript highlights the chaotic behaviors of the proposed cancer model for both the commensurate and the incommensurate cases.

A study on fractional HBV model through singular and non-singular derivatives.

The current study's aim is to evaluate the dynamics of a Hepatitis B virus (HBV) model with the class of asymptomatic carriers using two different numerical algorithms and various values of the fractional-order parameter. We considered the model with two different fractional-order derivatives, namely the Caputo derivative and Atangana-Baleanu derivative in the Caputo sense (ABC). The considered derivatives are the most widely used fractional operators in modeling.

A mathematical model for SARS-CoV-2 in variable-order fractional derivative.

A new coronavirus mathematical with hospitalization is considered with the consideration of the real cases from March 06, 2021 till the end of April 30, 2021. The essential mathematical results for the model are presented. We show the model stability when in the absence of infection.

Impact of information intervention on stochastic hepatitis B model and its variable-order fractional network.

This paper aims at analyzing the dynamical behavior of a SIR hepatitis B epidemic stochastic model via a novel approach by incorporating the effect of information interventions and random perturbations. Initially, we demonstrate the positivity and global existence of the solutions. Afterward, we derive the stochastic threshold parameter , followed by the fact that this number concludes the transmission of hepatitis B from the population.

Investigating the performance of dish solar distiller with phase change material mixed with AlO nanoparticles under different water depths.

The problem of potable water shortage all over the world made the scientists seek for solutions to overcome this problem. Solar distiller is one of the introduced solutions, but it demerited by the low freshwater output. In this proposed paper, a design modification includes the use of a convex dish absorber instead of the flat absorber liner.

A New Data-Driven Control System for MEMSs Gyroscopes: Dynamics Estimation by Type-3 Fuzzy Systems.

In this study, a novel data-driven control scheme is presented for MEMS gyroscopes (MEMS-Gs). The uncertainties are tackled by suggested type-3 fuzzy system with non-singleton fuzzification (NT3FS). Besides the dynamics uncertainties, the suggested NT3FS can also handle the input measurement errors.

Synchronization of the Glycolysis Reaction-Diffusion Model via Linear Control Law.

The Selkov system, which is typically employed to model glycolysis phenomena, unveils some rich dynamics and some other complex formations in biochemical reactions. In the present work, the synchronization problem of the glycolysis reaction-diffusion model is handled and examined. In addition, a novel convenient control law is designed in a linear form and, on the other hand, the stability of the associated error system is demonstrated through utilizing a suitable Lyapunov function.

Steel Wire Rope Surface Defect Detection Based on Segmentation Template and Spatiotemporal Gray Sample Set.

Machine-vision-based defect detection, instead of manual visual inspection, is becoming increasingly popular. In practice, images of the upper surface of cableway load sealing steel wire ropes are seriously affected by complex environments, including factors such as lubricants, adhering dust, natural light, reflections from metal or oil stains, and lack of defect samples. This makes it difficult to directly use traditional threshold-segmentation-based or supervised machine-learning-based defect detection methods for wire rope strand segmentation and fracture defect detection.

A Caputo-Fabrizio Fractional-Order Model of HIV/AIDS with a Treatment Compartment: Sensitivity Analysis and Optimal Control Strategies.

Although most of the early research studies on fractional-order systems were based on the Caputo or Riemann-Liouville fractional-order derivatives, it has recently been proven that these methods have some drawbacks. For instance, kernels of these methods have a singularity that occurs at the endpoint of an interval of definition. Thus, to overcome this issue, several new definitions of fractional derivatives have been introduced.

A novel fractional mathematical model of COVID-19 epidemic considering quarantine and latent time.

In this paper, we investigate the fractional epidemic mathematical model and dynamics of COVID-19. The Wuhan city of China is considered as the origin of the corona virus. The novel corona virus is continuously spread its range of effectiveness in nearly all corners of the world.

Combined open reduction and Dega transiliac osteotomy for developmental dysplasia of the hip in walking children.

The iliac osteotomy described by Dega in Poland, in 1969, is an acetabuloplasty that changes the acetabular configuration and its inclination. The aim of this work is to analyze a group of patients with DDH treated by combined open reduction and Dega transiliac osteotomy ,to evaluate the results and determine the advantages and disadvantages, as well as, assess the factors affecting the final outcome of such procedure. A prospective study was conducted during the period, from November 2010 to October 2014, on 39 hips, in 29 children, with neglected DDH after walking age, either diagnosed late or after failure to respond to previous non operative treatment.